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Background: Dedicated model transformation languages are claimed to provide many benefits over the use of general purpose languages for developing model transformations. However, the actual advantages and disadvantages associated with the use of model transformation languages are poorly understood empirically. There is little knowledge over what advantages and disadvantages hold in which cases and where they originate from. In a prior interview study, we elicited expert opinions on what advantages result from what factors surrounding model transformation languages as well as a number of moderating factors that moderate the influence. Objective: We aim to quantitatively asses the interview results to confirm or reject the influences and moderation effects posed by different factors and to gain insights into how valuable different factors are to the discussion. Method: We gather data on the factors and quality attributes using an online survey. To analyse the data and examine the hypothesised influences and moderations we use universal structure modelling based on a structural equation model. Universal structure modelling will produce significance values and path coefficients for each hypothesised and modelled interdependence between factors and quality attributes that can be used to confirm or reject correlation and to weigh the strength of influence present. Limitations: Due to the complexity and abstractness of the concepts under investigation, a measurement via reflective or formative indicators is not possible. Instead participants are queried about their assessment of concepts through a single item question. We further assume that positive and negative effects of a feature are more prominent if the feature is used more frequently.